Composite SaaS scaling in cloud computing using a hybrid genetic algorithm

A Software-as-a-Service or SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. Components in a composite SaaS may need to be scaled – replicated or deleted, to accommodate the user’s load. It may not be necessary to replicate all components of the SaaS, as some components can be shared by other instances. On the other hand, when the load is low, some of the instances may need to be deleted to avoid resource underutilisation. Thus, it is important to determine which components are to be scaled such that the performance of the SaaS is still maintained. Extensive research on the SaaS resource management in Cloud has not yet addressed the challenges of scaling process for composite SaaS. Therefore, a hybrid genetic algorithm is proposed in which it utilises the problem’s knowledge and explores the best combination of scaling plan for the components. Experimental results demonstrate that the proposed algorithm outperforms existing heuristic-based solutions.

Tensile properties of a boron/nitrogen-doped carbon nanotube–graphene hybrid structure

Doping is an effective approach that allows for the intrinsic modification of the electrical and chemical properties of nanomaterials. Recently, a graphene and carbon nanotube hybrid structure (GNHS) has been reported, which extends the excellent properties of carbon-based materials to three dimensions. In this paper, we carried out a first-time investigation on the tensile properties of the hybrid structures with different dopants. It is found that with the presence of dopants, the hybrid structures usually exhibit lower yield strength, Young’s modulus, and earlier yielding compared to that of a pristine hybrid structure. For dopant concentrations below 2.5% no significant reduction of Young’s modulus or yield strength could be observed. For all considered samples, the failure is found to initiate at the region where the nanotubes and graphene sheets are connected. After failure, monatomic chains are normally observed around the failure region. Dangling graphene layers without the separation of a residual CNT wall are found to adhere to each other after failure with a distance of about 3.4 Å. This study provides a fundamental understanding of the tensile properties of the doped graphene–nanotube hybrid structures, which will benefit the design and also the applications of graphene-based hybrid materials.

The Language : Rationale and Fundamentals

The Business Process Management domain has evolved at a dramatic pace over the past two decades and the notion of the business process has become a ubiquitous part of the modern business enterprise. Most organizations now view their operations in terms of business processes and manage these business processes in the same way as other corporate assets. In recent years, an increasingly broad range of generic technology has become available for automating business processes. This is part of a growing trend in the software engineering field throughout the past 40 years, where aspects of functionality that are potentially reusable on a widespread basis have coalesced into generic software components. Figure 2.1 illustrates this trend and shows how software systems have evolved from the monolithic applications of the 1960s developed in their entirety often by a single development team to today’s offerings that are based on the integration of a range of generic technologies with only a small component of the application actually being developed from scratch. In the 1990s, generic functionality for the automation of business processes first became commercially available in the form of workflow technology and subsequently evolved in the broader field of business process management systems (BPMS). This technology alleviated the necessity to develop process support within applications from scratch and provided a variety of off-the-shelf options on which these requirements could be based. The demand for this technology was significant and it is estimated that by 2000 there were well over 200 distinct workflow offerings in the market, each with a distinct conceptual foundation. Anticipating the difficulties that would be experienced by organizations seeking to utilize and integrate distinct workflow offerings, the Workflow Management Coalition (WfMC), an industry group formed to advance technology in this area, proposed a standard reference model for workflow technology with an express desire to seek a common platform for achieving workflow interoperation.

Generating natural language texts from business process models

Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

Hybrid frequency–time domain models for dynamic response analysis of marine structures

Time-domain models of marine structures based on frequency domain data are usually built upon the Cummins equation. This type of model is a vector integro-differential equation which involves convolution terms. These convolution terms are not convenient for analysis and design of motion control systems. In addition, these models are not efficient with respect to simulation time, and ease of implementation in standard simulation packages. For these reasons, different methods have been proposed in the literature as approximate alternative representations of the convolutions. Because the convolution is a linear operation, different approaches can be followed to obtain an approximately equivalent linear system in the form of either transfer function or state-space models. This process involves the use of system identification, and several options are available depending on how the identification problem is posed. This raises the question whether one method is better than the others. This paper therefore has three objectives. The first objective is to revisit some of the methods for replacing the convolutions, which have been reported in different areas of analysis of marine systems: hydrodynamics, wave energy conversion, and motion control systems. The second objective is to compare the different methods in terms of complexity and performance. For this purpose, a model for the response in the vertical plane of a modern containership is considered. The third objective is to describe the implementation of the resulting model in the standard simulation environment Matlab/Simulink.

An R2R3 MYB transcription factor determines red petal colour in an Actinidia (kiwifruit) hybrid population

Background Red colour in kiwifruit results from the presence of anthocyanin pigments. Their expression, however, is complex, and varies among genotypes, species, tissues and environments. An understanding of the biosynthesis, physiology and genetics of the anthocyanins involved, and the control of their expression in different tissues, is required. A complex, the MBW complex, consisting of R2R3-MYB and bHLH transcription factors together with a WD-repeat protein, activates anthocyanin 3-O-galactosyltransferase (F3GT1) to produce anthocyanins. We examined the expression and genetic control of anthocyanins in flowers of Actinidia hybrid families segregating for red and white petal colour. Results Four inter-related backcross families between Actinidia chinensis Planch. var. chinensis and Actinidia eriantha Benth. were identified that segregated 1:1 for red or white petal colour. Flower pigments consisted of five known anthocyanins (two delphinidin-based and three cyanidin-based) and three unknowns. Intensity and hue differed in red petals from pale pink to deep magenta, and while intensity of colour increased with total concentration of anthocyanin, no association was found between any particular anthocyanin data and hue. Real time qPCR demonstrated that an R2R3 MYB, MYB110a, was expressed at significant levels in red-petalled progeny, but not in individuals with white petals. A microsatellite marker was developed that identified alleles that segregated with red petal colour, but not with ovary, stamen filament, or fruit flesh colour in these families. The marker mapped to chromosome 10 in Actinidia. The white petal phenotype was complemented by syringing Agrobacterium tumefaciens carrying Actinidia 35S::MYB110a into the petal tissue. Red pigments developed in white petals both with, and without, co-transformation with Actinidia bHLH partners. MYB110a was shown to directly activate Actinidia F3GT1 in transient assays. Conclusions The transcription factor, MYB110a, regulates anthocyanin production in petals in this hybrid population, but not in other flower tissues or mature fruit. The identification of delphinidin-based anthocyanins in these flowers provides candidates for colour enhancement in novel fruits.

The Credit Act Advisory System (CAAS) : conversion from an expert system prototype to a C++ commercial system

CAAS is a rule-based expert system, which provides advice on the Victorial Credit Act 1984. It is currently in commercial use, and has been developed in conjunction with a law firm. It uses an object-oriented hybrid reasoning approach. The system was initially prototyped using the expert system shell NExpert Object, and was then converted into the C++ language. In this paper we describe the advantages that this methodology has, for both commercial and research development.

Broken gates and leaky graves : spectral language and Australia's ghost stories

Ghost stories are unusual amongst supernatural literatures in their modelling of a recognisable, mimetic reality interrupted or infiltrated by immaterial forces. In its discussion of Australian ghost stories, this thesis advances a new approach to ghost narratives which seeks to model and articulate the mechanics of ghosts and hauntings as something reliant on and engaged with the material and the mundane.

Understanding the information literacy experiences of EFL (English as a Foreign Language) students

This thesis investigated the information literacy experiences of EFL (English as a Foreign Language) students in a higher education institution in the United Arab Emirates (UAE). Phenomenography was used to investigate how EFL students' 'used information to learn' (ie. information literacy). The study revealed that EFL students' experienced information literacy across four categories and had varying experiences of information and learning. The research also showed that EFL students' faced a number of challenges and barriers due to language that impacted on their experiences of reading, understanding, accessing and translating information.

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Design of a garment for data collection of toddler language and physical activity

Design process phases of development, evaluation and implementation were used to create a garment to simultaneously collect reliable data of speech production and intensity of movement of toddlers (18-36 months). A series of prototypes were developed and evaluated that housed accelerometer-based motion sensors and a digital transmitter with microphone. The approved test garment was a top constructed from loop-faced fabric with interior pockets to house devices. Extended side panels allowed for sizing. In total, 56 toddlers (28 male; 28 female; 16-36 months of age) participated in the study providing pilot and baseline data. The test garment was effective in collecting data as evaluated for accuracy and reliability using ANOVA for accelerometer data, transcription of video for type of movement, and number and length of utterances for speech production. The data collection garment has been implemented in various studies across disciplines.

Educational paradox : the hidden obstacles to the integration of mobile phones in the language classroom

This paper reports on the findings of an international telecollaboration study using Facebook, in which teachers studying in M. Ed programs in Australia and Greece, discussed the use of mobile phones in language classrooms. Results suggest that invisible barriers exist in the use of mobile phones in the classroom, including bans on use in schools, lack of familiarity with educational uses for mobile phones, and negative perceptions about mobile phones specifically in terms of classroom management.

Hyperbranched polymer-gold nanoparticle assemblies : role of polymer architecture in hybrid assembly formation and SERS activity

Plasmonic gold nano-assemblies that self-assemble with the aid of linking molecules or polymers have the potential to yield controlled hierarchies of morphologies and consequently result in materials with tailored optical (e.g. localized surface plasmon resonances (LSPR)) and spectroscopic properties (e.g. surface enhanced Raman scattering (SERS)). Molecular linkers that are structurally well-defined are promising for forming hybrid nano-assemblies which are stable in aqueous solution and are increasingly finding application in nanomedicine. Despite much ongoing research in this field, the precise role of molecular linkers in governing the morphology and properties of the hybrid nano-assemblies remains unclear. Previously we have demonstrated that branched linkers, such as hyperbranched polymers, with specific anchoring end groups can be successfully employed to form assemblies of gold NPs demonstrating near-infrared SPRs and intense SERS scattering. We herein introduce a tailored polymer as a versatile molecular linker, capable of manipulating nano-assembly morphologies and hot-spot density. In addition, this report explores the role of the polymeric linker architecture, specifically the degree of branching of the tailored polymer in determining the formation, morphology and properties of the hybrid nano-assemblies. The degree of branching of the linker polymer, in addition to the concentration and number of anchoring groups, is observed to strongly influence the self-assembly process. The assembly morphology shifts primarily from 1D-like chains to 2D plates and finally to 3D-like globular structures, with increase in degree of branching. Insights have been gained into how the morphology influences the SERS performance of these nano-assemblies with respect to hot-spot density. These findings supplement the understanding of the morphology determining nano-assembly formation and pave the way for the possible application of these nano-assemblies as SERS bio-sensors for medical diagnostics.

A sparse hybrid map for vision-guided mobile robots

This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.